ADaComP: Adaptive residual gradient compression for data-parallel distributed training
- Chia-Yu Chen
- Jungwook Choi
- et al.
- 2018
- AAAI 2018
Publications
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56 results for Kailash Gopalakrishnan
INVITED: Accelerator Design for Deep Learning Training: Extended Abstract: Invited
- Ankur Agrawal
- Chia-Yu Chen
- et al.
- 2017
- DAC 2017
Deep learning with limited numerical precision
- Suyog Gupta
- Ankur Agrawal
- et al.
- 2015
- ICML 2015
Sub-30nm scaling and high-speed operation of fully-confined Access-Devices for 3D crosspoint memory based on mixed-ionic-electronic-conduction (MIEC) materials
- K. Virwani
- G.W. Burr
- et al.
- 2012
- IEDM 2012
Voltage polarity effects in GST-based phase change memory: Physical origins and implications
- A. Padilla
- G.W. Burr
- et al.
- 2010
- IEDM 2010
The Micro to Nano Addressing Block (MNAB)
- K. Gopalakrishnan
- R.S. Shenoy
- et al.
- 2005
- IEDM 2005
From DRAM to SRAM with a novel SiGe-based negative differential resistance (NDR) device
- Liang Yue
- Kailash Gopalakrishnan
- et al.
- 2005
- IEDM 2005
Accelerator Architectures and Machine Learning – AI Hardware
- Kailash Gopalakrishnan
- 2021
- DAC 2021
A 7-nm Four-Core Mixed-Precision AI Chip with 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling
- Sae Kyu Lee
- Ankur Agrawal
- et al.
- 2021
- IEEE JSSC
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization
- Andrea Fasoli
- Chia-Yu Chen
- et al.
- 2022
- INTERSPEECH 2022